
Data Engineer II at Hinge Health (Bengaluru-Hq)
Hinge Health· Bengaluru-Hq·
Role details
Hinge Health at a glance
Virtual physical therapy and musculoskeletal care that pairs licensed clinicians with 3D motion tracking and an FDA-cleared pain-relief wearable.
Hinge Health runs a digital clinic for muscle, joint, and pelvic pain. Members get a personalized exercise-therapy program plus a care team of physical therapists, health coaches, and orthopedic specialists, guided by computer-vision motion tracking and an FDA-cleared wearable. It sells to employers, health plans, and PBMs, who make the care available to members at no cost.
$1.46B raised · latest: IPO (NYSE: HNGE) - $437M - May 2025 · backed by Tiger Global Management, Coatue, Alkeon Capital, Whale Rock Capital Management
Job description
The Opportunity Data Engineers at Hinge Health are software engineers who specialize in building data pipelines, designing and implementing both OLTP and data warehouse schemas, data governance, ETL, RDBMS, and NoSQL systems. They create self-service tools and automation so application engineers and data scientists can manage their data independently and securely, following best practices for HIPAA compliance. The ideal candidate is self-driven and enjoys working in a highly collaborative, cross-functional environment. You will be working with a team of experienced data engineers who build and maintain a data platform that hosts petabytes of data. This platform supports key business decisions and powers important product features for our members. Our stack: Python, SQL, dbt, Metaplane, Airflow, PostgreSQL, REST, Docker,tonic.aiTonic.ai, Terraform, Spark, Kafka, Flink,Fivetran, Databricks, AWS (S3, RDS). Our workflow is trunk-based CI/CD, and our security/compliance posture is at the highest standards of healthcare, including HIPAA, HITRUST, SOC 2, CCPA.
What You’ll Accomplish
- Build and maintain batch and streaming data pipelines that deliver correct, on-time data to analytics and product teams.
- Implement dimensional data models and dbt transformations from a design that you and a senior engineer agree on.
- Add data quality tests, monitors, and alerts to the pipelines that you own. Respond when they fire.
- Apply the team's HIPAA and PII patterns when you handle member data. This includes access control, tagging, and audit trails.
- Diagnose and tune slow or expensive pipelines and queries. Report the cause and the measured improvement.
- Support business stakeholders and data scientists who use first-party and third-party data. Answer questions about the models that you build.
- Turn a business requirement into a technical design for one pipeline or one data model. Write it down before you build.
- Take part in on-call rotation for the data platform. Write and improve runbooks for the failures that you fix.
Hinge Health Hybrid Model We believe that remote work and in-person work have their own advantages and disadvantages, and we want to be able to leverage the best of both worlds. Employees in hybrid roles are required to be in the office 3 days/week. This is a Bengaluru-based role that involves regular interaction and collaboration with Hinge Health colleagues in San Francisco, CA.
- Time zones: San Francisco is in the Pacific Time Zone, which is 12 hours and 30 minutes behind India Standard Time (e.g., 8am in San Francisco is 8:30pm in Bengaluru).
- Hours: Applicants should be open to meetings in the late evening following India Standard Time to align with San Francisco working hours (8am - 6pm PT).
Basic Qualifications
- Bachelor’s Degree in Computer Science or related technical degree
- 3+ years of data engineering experience
- 2+ years of experience in processing and storing large scale data using distributed systems as well as working knowledge of database designs and data warehousing including star and snowflake schemas.
- 2+ years of experience working with broad spectrum of OLTP data stores like PostgreSQL,MySQL, MongoDB, Redis and OLAP stores like Databricks,Snowflake, Redshift
- 1+ years of experience building data pipelines using Spark, Kafka, Airflow
- 1+ years of experience designing and implementing data warehouse models (e.g., STAR, Snowflake), as well as developing ELT and ETL pipelines within data lake ecosystems
Preferred Qualifications
- Mastery of SQL and Python
- Working knowledge of IAC like terraform
- Excellent verbal and written communication skills, especially in communicating complex technical problems with non-technical stakeholders
- 1+ year experience working with dbt
- Knowledge of streaming systems like Flink, Kafka streams or spark streaming
- Experience with managed data integration platforms like Fivetran,Estuary
- Experience building data products that serve machine learning: feature pipelines, training datasets, or model-serving inputs.
- Daily use of AI coding assistants, and interest in AI-powered self-serve analytics such as natural-language query over a data warehouse.
About Hinge Health
At Hinge Health, we’re using technology to scale and automate the delivery of healthcare – starting with musculoskeletal (MSK) conditions, which affect over 1.7 billion people worldwide. With an AI-powered human-centered care model, Hinge Health leverages cutting-edge technology to improve outcomes, experiences and costs to help people move beyond their pain. The platform addresses a broad spectrum of MSK care – from acute injury, to chronic pain, to post-surgical rehabilitation – through personalized, evidence-based care. As the preferred partner to 50+ health plans, PBMs and other ecosystem partners, Hinge Health is available to over 20 million people across more than 2,550 employers. The company is headquartered in San Francisco with additional offices in Montreal and Bangalore. Learn more athingehealth.com/www.hingehealth.com
What You'll Love About Us
- Inclusive healthcare and benefits: In addition to comprehensive medical, dental, and vision coverage, we provide employees and their family members with Group Medical Coverage (GMC), Group Term Life Insurance (GTL), and Group Personal Accident Insurance (GPA).
- We also offer a lifestyle stipend to support your overall well-being, along with learning and development opportunities to help you grow both personally and professionally.
- Grow with us through discounted company stock through our ESPP with easy payroll deductions.
Culture and Engagement Hinge Health is an equal opportunity employer and prohibits discrimination and harassment of any kind. We make employment decisions without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, pregnancy, or any other basis protected by federal, state or local law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We provide reasonable accommodations for candidates with disabilities. If you feel you need assistance or an accommodation due to a disability, let us know by reaching out to your recruiter. By submitting your application you are acknowledging we are using your personal data as outlined in the personnel and candidate privacy policy.
Beware of Phishing Attempts: We've noticed an increase in phishing where fraudsters impersonate employees and send fake job offers to steal sensitive information. We'll never ask for financial details during the hiring process and only use "@hingehealth.com" emails. If you receive a suspicious offer, stop communication and report it to the US FBI Internet Crime Complaint Center. To verify an email from our recruiting team, forward it to security@hingehealth.com.
Why work at Hinge Health
- Culture: Emphasis on autonomy, mastery, and purpose. The R&D blog describes an environment where engineers review reasoning logs instead of diffs and where AI agents ship PRs without human line edits.
- Work Model: Hybrid/office presence – HQ in San Francisco with offices in India, Canada, UK, and Colombia. Specific remote policy not detailed in sources.
- Impact: Opportunity to work on regulatory-grade AI that directly improves clinical outcomes for millions of people.
- Reviews: Employer rating of 3.8/5 on LinkedIn; strong scores for work-life balance (3.7) and compensation (3.7).
- Notable Perks: Not explicitly listed, but the culture of “impact at scale” and investment in R&D suggests strong engineering support.